Data Quality Specialist

Role Overview

We are seeking a Data Quality Specialist to lead the execution and adoption of a Data Quality Governance Framework within our organization. This role involves defining and maintaining comprehensive data quality rules, controls, standards, and procedures. The specialist will collaborate closely with business stakeholders to grasp data quality needs and translate those into actionable requirements.

Key Responsibilities

• Lead the implementation and promotion of the Data Quality Governance Framework throughout the project.
• Define, uphold, and refine data quality rules, controls, standards, and processes to ensure data integrity.
• Engage with business users to understand their data quality requirements and business needs.
• Conduct thorough data analysis, profiling, validation, and root cause investigations to identify data quality issues.
• Track and manage data quality issues, driving them towards resolution.
• Establish and monitor key performance indicators (KPIs) for data quality and generate relevant reports.
• Collaborate with delivery teams to guarantee accurate implementation of business logic and data quality requirements.
• Provide support during system integration testing (SIT), user acceptance testing (UAT), and production data validation stages.
• Raise awareness and foster governance of data quality across the project landscape.

Qualifications and Experience

• Proven background in Data Quality, Data Governance, Business Analysis, Analytics, or similar functions.
• Strong capabilities in stakeholder engagement and facilitation.
• Experienced in converting business expectations into concrete data quality and data-related requirements.
• Excellent analytical thinking and problem-solving skills.
• Skilled in diagnosing data anomalies and conducting root cause analyses.
• Ability to collaborate effectively with both technical teams and business units.
• Superior communication and documentation abilities.

Preferred Skills

• Proficiency in SQL for data analysis and validation tasks.
• Understanding of data integration processes, including ETL/ELT and data pipeline concepts.
• Experience with analytics and business intelligence platforms such as Power BI.
• Knowledge of data governance, metadata management, and data lineage principles.